软件测试论文.doc

沈阳理工大学高等职业技术学院论文
题目: 黑盒测试方法研究
系别: 信息控制学院
专业: 计算机科学与技术
学生姓名: 软件测试
指导教师: 孙承福
2011年 04 月 26 日
摘要
黑盒测试提出了一种利用遗传算法帮助测试人员在较短时间内完成软件模块的黑盒测试,并给出测试结果和好的测试用例的方法。
在软件测试中,黑盒测试主要是针对模块进行的功能测试。最普遍的方法是以软件的功能说明书为基础将软件的输入划分为若干个等价类,多次运行该软件来检验软件对于不同的等价类是否能满足要求。但是在实际应用中,有的模块太大或输入参数太多,等价类划分后需要进行的测试工作可能是一个极大的任务。这时,如何选择最优的测试用例就成为测试人员的一个重要任务。
  遗传算法是模仿生物遗传和进化机制的一种最优化方法,它把类似于遗传基因的一些行为,如交叉重组、变异、选择和淘汰等引入到算法求解的改进过程中。遗传算法的特点之一是,它同时保留着若干局部最优解,通过交叉重组或者解的变异来寻求更好的解。与贪婪算法相比,遗传算法更可能找到全局最优解,而贪婪算法则容易限于局部最优而达不到全局最优。
如果能够将遗传算法有效地运用于黑盒测试中,帮助测试人员选择最优的测试用例,那么将给测试工作带来极大的帮助。[1]
关键字:黑盒测试;测试用例;耦合度
Abstract
Black box testing proposes a kind of ic algorithms are used to help testers in shorter plete software module black box testing, and gives the test results and good method of test case.
In testing, the black box testing is mainly aimed at modules. Functional testing The mon method is based software function specification of input software divided into several equivalence class, repeatedly run this software to test software for different equivalence class if you can meet the requirements. But in practical applications, some module is too large or input parameter too much, equivalence partitioning needs after test work may be a huge task. Then, how to select the optimal test cases will e an important task of the testers.
ic algorithm is imitate biological ics and evolutionary mechanism of a kind of optimization methods, it is similar to some of the ic gene behaviour, such as cross restructuring, variation, selection and out into the algorithm for solving such improvement process. One of the characteristics of ic algorithm, it also retains several local optimal solution, through cross restructuring or solution variation to seek a better solution. Compared with greedy algorithm, ic algorithm is more likely to find the optimal solution, and it's easier to greedy algorithm to local optimal and short of global optimal.
If can the ic algorithm is effective use in black box testing, help testers selecti